From f84d37dd304de3e2b299523a89b3127bc5c3600f Mon Sep 17 00:00:00 2001
From: Elias Projahn <elias@johrpan.de>
Date: Tue, 16 Nov 2021 16:23:03 +0100
Subject: [PATCH] neural: Readd distances as input data

---
 R/analyze.R |  7 +++++--
 R/neural.R  | 28 +++++++++++++++++++---------
 2 files changed, 24 insertions(+), 11 deletions(-)

diff --git a/R/analyze.R b/R/analyze.R
index 33a84f5..2fb865a 100644
--- a/R/analyze.R
+++ b/R/analyze.R
@@ -40,8 +40,11 @@ analyze <- function(preset, progress = NULL) {
         "correlation_positions" = function(...) {
             correlation(..., use_positions = TRUE)
         },
-        "proximity" = proximity,
-        "neural" = neural
+        "neural" = neural,
+        "neural_positions" = function(...) {
+            neural(..., use_positions = TRUE)
+        },
+        "proximity" = proximity
     )
 
     results <- cached("analysis", preset, {
diff --git a/R/neural.R b/R/neural.R
index 730300c..2987ed1 100644
--- a/R/neural.R
+++ b/R/neural.R
@@ -1,14 +1,17 @@
 # Find genes by training a neural network on reference position data.
 #
 # @param seed A seed to get reproducible results.
-neural <- function(preset, progress = NULL, seed = 448077) {
+neural <- function(preset,
+                   use_positions = FALSE,
+                   progress = NULL,
+                   seed = 448077) {
     species_ids <- preset$species_ids
     gene_ids <- preset$gene_ids
     reference_gene_ids <- preset$reference_gene_ids
 
     cached(
         "neural",
-        c(species_ids, gene_ids, reference_gene_ids),
+        c(species_ids, gene_ids, reference_gene_ids, use_positions),
         { # nolint
             set.seed(seed)
             gene_count <- length(gene_ids)
@@ -28,10 +31,17 @@ neural <- function(preset, progress = NULL, seed = 448077) {
 
             # Make a column containing positions for each species.
             for (species_id in species_ids) {
-                species_data <- distances[
-                    species == species_id,
-                    .(gene, position)
-                ]
+                species_data <- if (use_positions) {
+                    setnames(distances[
+                        species == species_id,
+                        .(gene, position)
+                    ], "position", "distance")
+                } else {
+                    distances[
+                        species == species_id,
+                        .(gene, distance)
+                    ]
+                }
 
                 # Only include species with at least 25% known values.
 
@@ -48,11 +58,11 @@ neural <- function(preset, progress = NULL, seed = 448077) {
                     # However, this will of course lessen the significance of
                     # the results.
 
-                    mean_position <- round(species_data[, mean(position)])
-                    data[is.na(position), position := mean_position]
+                    mean_distance <- round(species_data[, mean(distance)])
+                    data[is.na(distance), distance := mean_distance]
 
                     # Name the new column after the species.
-                    setnames(data, "position", species_id)
+                    setnames(data, "distance", species_id)
                 }
             }